Artificial Intelligence and Network Medicine: Path to Precision Medicine.

Area of Science:

• Biomedical Informatics
• Computational Biology
• Systems Biology

Background:

• Network medicine (NM) has advanced disease mechanism elucidation, drug target identification, and precision therapy development over 20 years.
• The integration of artificial intelligence (AI), especially deep learning, with NM is a growing area with significant therapeutic potential.

Purpose of the Study:

• To review the combined use of AI and NM for advancing precision medicine.
• To illustrate the successes and challenges of integrating AI and NM in analyzing complex biomedical data.

Main Methods:

• Review of current literature on AI and NM integration.
• Analysis of multiomic datasets using combined AI and NM approaches.
• Exploration of deep learning techniques within the network medicine framework.

Main Results:

• The synergy of AI and NM enhances the speed and predictive precision of computational analyses.
• Combined approaches yield deeper biological insights from large multiomic datasets.
• Successful applications demonstrate the potential for elucidating complex disease mechanisms.

Conclusions:

• The integration of AI and NM offers a powerful computational strategy for precision medicine.
• This combined approach is crucial for navigating the complexity of multiomic data.
• Ongoing challenges in AI-NM integration require further research and development.